code: def test_weight_transfer_include_top(self, keras_name, objax_name):
      model_keras = getattr(tf.keras.applications, keras_name)(
          include_top=True,
          weights=None,
          classes=1000,
          classifier_activation="linear",
      )
      model_objax = objax.zoo.resnet_v2.__dict__[objax_name](
          in_channels=3,
          num_classes=1000,
          normalization_fn=partial(
              objax.nn.BatchNorm2D, momentum=0.99, eps=1.001e-05
          ),
      )
      convert_keras_model(
          model_keras,
          model_objax,
          model_registry[objax_name]["num_blocks"],
          True,
      )
      self.check_compatibility(model_keras, model_objax)
      self.check_output_shape(model_objax, 1000)
  
file_path: objax/tests/resnet_v2.py
imports: import unittest
  from parameterized import parameterized
  from functools import partial
  import numpy
  import tensorflow
  import objax
  from objax.zoo.resnet_v2 import ResNet18, ResNet34, ResNet50, ResNet101, ResNet152, ResNet200
  from objax.zoo.resnet_v2 import convert_keras_model, load_pretrained_weights_from_keras
label_desc: Use image node_id 4 for calling the TestResNetV2Pretrained obj's underlying member method code with example usage: obj.test_weight_transfer_include_top(keras_name, objax_name) without return types